Multivariate data analysis on historical IPV production data for better process understanding and future improvements
Abstract
Historical manufacturing data can potentially harbor a wealth of information for process optimization and enhancement of efficiency and robustness. To extract useful data multivariate data analysis (MVDA) using projection methods is often applied. In this contribution, the results obtained from applying MVDA on data from inactivated polio vaccine (IPV) production runs are described. Data from over 50 batches at two different production scales (700-L and 1,500-L) were available. The explorative analysis performed on single unit operations indicated consistent manufacturing. Known outliers (e.g., rejected batches) were identified using principal component analysis (PCA). The source of operational variation was pinpointed to variation of input such as media. Other relevant process parameters were in control and, using this manufacturing data, could not be correlated to product quality attributes. The gained knowledge of the IPV production process, not only from the MVDA, but also from digitalizing the available historical data, has proven to be useful for troubleshooting, understanding limitations of available data and seeing the opportunity for improvements.
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MVA was used to supplement univariate analysis, and PCA was useful for process trouble shooting and comparison between data sets.
“MVA was used to supplement univariate analysis, and the PCA was useful for process trouble shooting and comparison between data sets [80].”
From Factors Affecting Microalgae Production for Biofuels and the Potentials of Chemometric Methods in Assessing and Optimizing Productivity (2019) · cites this paper as [80]
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- Authors
- Thomassen, Y. E., van Sprang, E. N. M., van der Pol, L. A., & Bakker, W. A. M.
- Corresponding author
- Thomassen, Yvonne E.
- Venue
- Biotechnology and Bioengineering
- Publisher
- Wiley
- Published
- 2010-06-11
- Volume
- 107
- Issue
- 1
- Pages
- 96-104
- ISSN
- 0006-3592 (ISSN-L)
- 1097-0290
- OpenAlex
- W1995581041
- Cited by
- 46
- References
- 20
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 2 · 2023: 2 · 2021: 2 · 2020: 3 · 2019: 3 · 2017: 2 · 2016: 5 · 2015: 4 · 2014: 4 · 2013: 7 · 2012: 3
- FWCI
- 9.01
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Biotechnology and Bioengineering (publishedVersion)
- PubMed (publishedVersion)
- Rivm (National Institute for Public Health and the Environment) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Fault Detection and Control Systems
- Physical Sciences › Chemistry › Analytical Chemistry › Spectroscopy and Chemometric Analyses
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Viral Infectious Diseases and Gene Expression in Insects
- Keywords
- inactivated poliovirus vaccine, vaccine production, multivariate analysis, principal component analysis, outlier detection, process variation, process understanding, process optimization, troubleshooting
- MeSH terms
- Animals, Chlorocebus aethiops, Data Interpretation, Statistical, Forecasting, Industry, Models, Biological, Poliovirus Vaccine, Inactivated, Vero Cells, Multivariate Analysis
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